随机条件下交叉口感应信号控制优化研究

发布时间：2018-05-05 04:13

本文选题：感应控制 + 随机条件　；参考：《兰州交通大学》2014年硕士论文

【摘要】：城市交叉口信号控制形式主要分为定时控制和感应控制，后者根据检测器测到的实时交通信息动态控制信号灯显示状态，克服了定时控制固定配时方案的缺陷，感应控制系统的部署应是今后的发展趋势。通过对感应信号控制进行深入研究，不仅可以有效提高道路通行能力，缓解目前普遍存在的交通拥堵问题，减少交通事故发生率，而且能够在一定程度上减轻交通污染。感应控制的配时参数和控制策略对最终控制效果起着决定性作用，论文选择对这两个核心内容进行研究，考虑了交通流的随机特性，分别建立了最小绿灯时间、最大绿灯时间、控制逻辑的优化模型和方法。论文首先分析了已有感应控制中配时参数的确定方法和研究现状，目前在对感应控制两个主要配时参数最小绿灯时间和最大绿灯时间进行确定时，都未考虑到交通流的随机特性，假定车辆到达服从均匀分布，这与实际并不相符，控制效果和期望值还有一定距离。其次，针对已有研究存在的不足，考虑车辆到达的随机性，以交叉口平均延误最小为目标函数，考虑车辆安全行驶、行人过街时间和周期时长约束条件，建立了最小绿灯时间优化模型，并用拉格朗日解析法给出了求解最小绿灯时间的解析算法，运用随机模拟逼近目标函数的方法求解各相位最小绿灯时间的最优值；其次，分析了随机车流车头时距和绿灯延长时间的关系，分别考虑各种情况下绿灯延长的概率，根据各自概率和对应的绿灯时间建立了最大绿灯时间优化模型。然后，在分析定时控制动态相序控制的基础上，提出了感应控制基于相位关键进口道排队长度的相序优化方法，，为避免出现某些相位的过饱和排队而无法立即得到通行权的现象发生，以相位关键进口道车辆排队长度为选择依据，选择其中最长的相位作为下一通行相位，保证对绿灯时间的有效利用。最后，用VISSIM感应控制模块对提出的模型进行了仿真验证，分别对优化后配时参数和控制逻辑进行仿真，和传统感应控制进行对比，仿真结果表明在车辆到达服从二项分布和泊松分布时，提出的模型在不同饱和度情况下交叉口各评价指标都有不同程度的改善，具有较好的控制效果。
[Abstract]:The signal control forms of urban intersections are mainly divided into timing control and induction control. The latter can dynamically control the signal display state according to the real-time traffic information measured by the detector, which overcomes the defects of the fixed timing control scheme of timing control. The deployment of induction control system should be the development trend in the future. Through the in-depth study of the induction signal control, not only can the road traffic capacity be effectively improved, the current traffic congestion problem can be alleviated, the traffic accident rate can be reduced, but also the traffic pollution can be alleviated to a certain extent. The timing parameters and control strategies of induction control play a decisive role in the final control effect. This paper chooses to study these two core contents, considers the stochastic characteristics of traffic flow, and establishes the minimum green time and the maximum green time, respectively. Optimization model and method of control logic. At first, the paper analyzes the methods and research status of the timing parameters in the induction control. At present, the minimum green time and the maximum green time of the two main timing parameters of the induction control are determined. The random characteristics of traffic flow are not taken into account and the uniform distribution of vehicle arrival clothes is assumed which is not in accordance with the actual situation. The control effect and expected value are still far away. Secondly, considering the randomness of vehicle arrival, taking the minimum average delay at intersection as objective function, considering the limitations of vehicle safety, pedestrian crossing time and cycle time, The optimization model of minimum green time is established, and an analytical algorithm for solving the minimum green time is given by using Lagrange analytical method. The optimal value of minimum green time of each phase is obtained by using stochastic approximation of objective function. Based on the analysis of the relationship between the headway time of random traffic flow and the extended time of green light, considering the probability of green light extension under various conditions, the optimization model of maximum green time is established according to their respective probability and corresponding green time. Then, on the basis of analyzing the dynamic phase sequence control of timing control, a phase sequence optimization method based on phase critical inlet queue length is proposed. In order to avoid the phenomenon of oversaturated queue of some phases and the failure to obtain the traffic right immediately, the longest phase is chosen as the next phase based on the queue length of the vehicle with critical phase entrance. Ensure the efficient use of green time. Finally, the proposed model is simulated with the VISSIM induction control module, and the optimized post-timing parameters and control logic are simulated, and compared with the traditional induction control. The simulation results show that when the vehicle arrival clothes are distributed from binomial distribution and Poisson distribution, the evaluation indexes of the proposed model are improved to different extent under different saturation conditions, and the model has better control effect.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491.54

【参考文献】